The pragmatic proof: hypermedia API composition and execution

Machine clients are increasingly making use of the Web to perform tasks. While Web services traditionally mimic remote procedure calling interfaces, a new generation of so-called hypermedia APIs works through hyperlinks and forms, in a way similar to how people browse the Web. This means that existing composition techniques, which determine a procedural plan upfront, are not sufficient to consume hypermedia APIs, which need to be navigated at runtime. Clients instead need a more dynamic plan that allows them to follow hyperlinks and use forms with a preset goal. Therefore, in this paper, we show how compositions of hypermedia APIs can be created by generic Semantic Web reasoners. This is achieved through the generation of a proof based on semantic descriptions of the APIs' functionality. To pragmatically verify the applicability of compositions, we introduce the notion of pre-execution and post-execution proofs. The runtime interaction between a client and a server is guided by proofs but driven by hypermedia, allowing the client to react to the application's actual state indicated by the server's response. We describe how to generate compositions from descriptions, discuss a computer-assisted process to generate descriptions, and verify reasoner performance on various composition tasks using a benchmark suite. The experimental results lead to the conclusion that proof-based consumption of hypermedia APIs is a feasible strategy at Web scale.Peer ReviewedPostprint (author's final draft

Information Technology, Workplace Organization and the Demand for Skilled Labor: Firm-Level Evidence

Recently, the relative demand for skilled labor has increased dramatically. We investigate one of the causes, skill-biased technical change. Advances in information technology (IT) are among the most powerful forces bearing on the economy. Employers who use IT often make complementary innovations in their organizations and in the services they offer. Our hypothesis is that these co-inventions by IT users change the mix of skills that employers demand. Specifically, we test the hypothesis that it is a cluster of complementary changes involving IT, workplace organization and services that is the key skill-biased technical change. We examine new firm-level data linking several indicators of IT use, workplace organization, and the demand for skilled labor. In both a short-run factor demand framework and a production function framework, we find evidence for complementarity. IT use is complementary to a new workplace organization which includes broader job responsibilities for line workers, more decentralized decision-making, and more self-managing teams. In turn, both IT and that new organization are complements with worker skill, measured in a variety of ways. Further, the managers in our survey believe that IT increases skill requirements and autonomy among workers in their firms. Taken together, the results highlight the roles of both IT and IT-enabled organizational change as important components of the skill-biased technical change.

MAGDA: A Mobile Agent based Grid Architecture

Mobile agents mean both a technology and a programming paradigm. They allow for a flexible approach which can alleviate a number of issues present in distributed and Grid-based systems, by means of features such as migration, cloning, messaging and other provided mechanisms. In this paper we describe an architecture (MAGDA – Mobile Agent based Grid Architecture) we have designed and we are currently developing to support programming and execution of mobile agent based application upon Grid systems

Bio-Inspired Hybrid Algorithm for Web Services Clustering

Web services clustering is the task of extracting and selecting the features from a collection of Web services and forming groups of closely related services. The implementation of novel and efficient algorithms for Web services clustering is relevant for the organization of service repositories on the Web. Counting with well-organized collections of Web services promotes the efficiency of Web service discovery, search, selection, substitution, and invocation. In recent years, methods inspired by nature using biological analogies have been adapted for clustering problems, among which genetic algorithms, evolutionary strategies, and algorithms that imitate the behavior of some animal species have been implemented. Computation inspired by nature aims at imitating the steps that nature has developed and adapting them to find a solution of a given problem. In this chapter, we investigate how biologically inspired clustering methods can be applied to clustering Web services and present a hybrid approach for Web services clustering using the Artificial Bee Colony (ABC) algorithm, K-means, and Consensus. This hybrid algorithm was implemented, and a series of experiments were conducted using three collections of Web services. Results of the experiments show that the solution approach is adequate and efficient to carry out the clustering of very large collections of Web services